Learn to optimize your AI compute budget by distilling a complete, complex multi-agent intelligence system into a single efficient agent through this 26-minute tutorial. Explore three different distillation techniques and examine their performance benchmarks for creating a small LLM suitable for local deployment. Discover how to consolidate the capabilities of five AI agents into one streamlined solution while maintaining effectiveness. Access the accompanying code implementation and understand the methodology behind AgentArk research from Carnegie Mellon University, William & Mary, Georgia Institute of Technology, Amazon, and University of British Columbia that demonstrates practical approaches to multi-agent intelligence compression.